Sotabase

Career

· Vice President of Research, Google DeepMind2021–
· Chief Scientist, Uber2017–2021
· Deputy Academic Director, Leverhulme Centre for the Future of Intelligence2016–
· Co-Director, Uber AI Labs2016–2021
· Co-Director, Alan Turing Institute for Data Science2015–2017
· Adjunct Professor, Pohang University of Science and Technology (POSTECH)2007–2010
· Professor of Information Engineering, University of Cambridge2006–
· Associate Research Professor in Machine Learning, Carnegie Mellon University2003–2012
· Faculty Member, Gatsby Computational Neuroscience Unit, University College London1998–2005
· PhD in Cognitive Neuroscience, Massachusetts Institute of Technology1995–1995
· Postdoctoral Researcher, University of Toronto1995–1998
· Student (B.S.Eng. in Computer Science and Engineering), University of Pennsylvania1990–1990

Publications (440)

Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning
International Conference on Machine Learning · 2015
10,867
cited
An Introduction to Variational Methods for Graphical Models
Machine-mediated learning · 1999
4,593
cited
Combining active learning and semi-supervised learning using Gaussian fields and harmonic functions
International Conference on Machine Learning · 2003
3,510
cited
An internal model for sensorimotor integration.
Science · 1995
3,465
cited
Active Learning with Statistical Models
Neural Information Processing Systems · 1996
2,503
cited
Computational principles of movement neuroscience
Nature Neuroscience · 2000
2,082
cited
Sparse Gaussian Processes using Pseudo-inputs
Neural Information Processing Systems · 2005
1,984
cited
Probabilistic machine learning and artificial intelligence
Nature · 2015
1,949
cited
Learning from labeled and unlabeled data with label propagation
2002
1,896
cited
Deep Bayesian Active Learning with Image Data
International Conference on Machine Learning · 2017
1,892
cited
A Theoretically Grounded Application of Dropout in Recurrent Neural Networks
Neural Information Processing Systems · 2015
1,701
cited
MASSACHUSETTS INSTITUTE OF TECHNOLOGY ARTIFICIAL INTELLIGENCE LABORATORY and CENTER FOR BIOLOGICAL AND COMPUTATIONAL LEARNING DEPARTMENT OF BRAIN AND COGNITIVE SCIENCES
1996
1,223
cited
Kronecker Graphs: An Approach to Modeling Networks
Journal of machine learning research · 2008
1,111
cited
A Unifying Review of Linear Gaussian Models
Neural Computation · 1999
1,071
cited
Bayesian Active Learning for Classification and Preference Learning
arXiv.org · 2011
1,022
cited
Infinite latent feature models and the Indian buffet process
Neural Information Processing Systems · 2005
853
cited
An Introduction to Hidden Markov Models and Bayesian Networks
International journal of pattern recognition and artificial intelligence · 2001
843
cited
Bayesian Convolutional Neural Networks with Bernoulli Approximate Variational Inference
arXiv.org · 2015
806
cited
Simultaneous Localization and Mapping with Sparse Extended Information Filters
Int. J. Robotics Res. · 2004
781
cited
The EM algorithm for mixtures of factor analyzers
1996
780
cited
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